Low pH inactivation of enveloped viruses has historically been shown to be an effective viral inactivation step in biopharmaceutical manufacturing. To date, most statistical analyses supporting modular low pH viral inactivation claims have used descriptive statistical analyses, which in many cases do not allow for probabilistic characterization of future experimental log reduction values (LRVs). Using Bayesian hierarchical logistic regression modeling, probability statements regarding the likelihood of successful low pH viral inactivation based on only certain process parameter settings can be derived.
View Article and Find Full Text PDFVirus filtration provides robust removal of potential viral contaminants and is a critical step during the manufacture of biotherapeutic products. However, recent studies have shown that small virus removal can be impacted by low operating pressure and depressurization. To better understand the impact of these conditions and to define robust virus filtration design spaces, we conducted multivariate analyses to evaluate parvovirus removal over wide ranges of operating pressure, solution pH, and conductivity for three mAb products on Planova™ BioEX and 20N filters.
View Article and Find Full Text PDFSeveral nucleic-acid based technologies have recently emerged with capabilities for broad virus detection. One of these, high throughput sequencing, has the potential for novel virus detection because this method does not depend upon prior viral sequence knowledge. However, the use of high throughput sequencing for testing biologicals poses greater challenges as compared to other newly introduced tests due to its technical complexities and big data bioinformatics.
View Article and Find Full Text PDFPDA J Pharm Sci Technol
January 2014
PDA J Pharm Sci Technol
April 2016
CONFERENCE PROCEEDING Proceedings of the PDA/FDA Adventitious Viruses in Biologics: Detection and Mitigation Strategies Workshop in Bethesda, MD, USA; December 1-3, 2010 Guest Editors: Arifa Khan (Bethesda, MD), Patricia Hughes (Bethesda, MD) and Michael Wiebe (San Francisco, CA).
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